Evaluating Random Forests for Survival Analysis using Prediction Error Curves [0.03%]
使用预测误差曲线评估生存分析中的随机森林方法
Ulla B Mogensen,Hemant Ishwaran,Thomas A Gerds
Ulla B Mogensen
Prediction error curves are increasingly used to assess and compare predictions in survival analysis. This article surveys the R package pec which provides a set of functions for efficient computation of prediction error curves. The softwar...
Exact and Asymptotic Weighted Logrank Tests for Interval Censored Data: The interval R package [0.03%]
具有区间删失数据的精确和渐近加权Logrank检验：intervalR软件包
Michael P Fay,Pamela A Shaw
Michael P Fay
For right-censored data perhaps the most commonly used tests are weighted logrank tests, such as the logrank and Wilcoxon-type tests. In this paper we review several generalizations of those weighted logrank tests to interval-censored data ...
isocir: An R Package for Constrained Inference using Isotonic Regression for Circular Data, with an Application to Cell Biology [0.03%]
基于圆数据约束推断的等顿回归R包Isocir及其在细胞生物学中的应用
Sandra Barragán,Miguel A Fernández,Cristina Rueda et al.
Sandra Barragán et al.
In many applications one may be interested in drawing inferences regarding the order of a collection of points on a unit circle. Due to the underlying geometry of the circle standard constrained inference procedures developed for Euclidean ...
Sheng Luo,Yong Chen,Xiao Su et al.
Sheng Luo et al.
This paper describes the core features of the R package mmeta, whichimplements the exact posterior inference of odds ratio, relative risk, and risk difference given either a single 2 × 2 table or multiple 2 × 2 tables when the risks withi...
SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models [0.03%]
SNP_NLMM：用于实现广义线性和非线性混合模型的灵活随机效应密度的SAS宏程序
David M Vock,Marie Davidian,Anastasios A Tsiatis
David M Vock
Generalized linear and nonlinear mixed models (GMMMs and NLMMs) are commonly used to represent non-Gaussian or nonlinear longitudinal or clustered data. A common assumption is that the random effects are Gaussian. However, this assumption m...
GLIMMPSE: Online Power Computation for Linear Models with and without a Baseline Covariate [0.03%]
具有或不具有基线协变量的线性模型的在线功效计算(GLIMMPSE)
Sarah M Kreidler,Keith E Muller,Gary K Grunwald et al.
Sarah M Kreidler et al.
GLIMMPSE is a free, web-based software tool that calculates power and sample size for the general linear multivariate model with Gaussian errors (http://glimmpse.SampleSizeShop.org/). GLIMMPSE provides a user-friendly interface for the comp...
David R Hunter,Steven M Goodreau,Mark S Handcock
David R Hunter
Exponential-family random graph models (ERGMs) represent a powerful and flexible class of models for the statistical analysis of networks. statnet is a suite of software packages that implement these models. This paper details how the capab...
Donald Hedeker,Rachel Nordgren
Donald Hedeker
MIXREGLS is a program which provides estimates for a mixed-effects location scale model assuming a (conditionally) normally-distributed dependent variable. This model can be used for analysis of data in which subjects may be measured at man...
DiagTest3Grp: An R Package for Analyzing Diagnostic Tests with Three Ordinal Groups [0.03%]
DiagTest3Grp：一个用于分析三个有序组诊断试验结果的R软件包
Jingqin Luo,Chengjie Xiong
Jingqin Luo
Medical researchers endeavor to identify potentially useful biomarkers to develop marker-based screening assays for disease diagnosis and prevention. Useful summary measures which properly evaluate the discriminative ability of diagnostic m...
Peter Langfelder,Steve Horvath
Peter Langfelder
Many high-throughput biological data analyses require the calculation of large correlation matrices and/or clustering of a large number of objects. The standard R function for calculating Pearson correlation can handle calculations without ...